How to Use the Moonscan (Moonbeam Network Explorer) MCP in LlamaIndex

Q: How do I connect Moonscan (Moonbeam Network Explorer) tools to a LlamaIndex agent using an MCP client?

Use the llama-index-tools-mcp library to initialize the client with your Vinkius URL. Convert the server's tools into a tool spec and pass them to your FunctionAgent. This exposes all 26 endpoints, including getglmrbalance, to your agent.

Q: Can I index ERC-20 balances retrieved from Moonscan (Moonbeam Network Explorer) into LlamaIndex?

Yes, you can fetch token data using geterc20balance and insert the resulting balance data directly into your vector index. This allows your RAG pipeline to retrieve updated financial profiles for target addresses on demand.

Q: How does LlamaIndex handle large transaction logs from Moonscan (Moonbeam Network Explorer)?

When calling getlogs, the output can be large, so you should use LlamaIndex's node parsers to chunk the data. This prevents your LLM context window from overflowing while keeping the transaction details searchable.

Q: Does this server support checking contract execution status?

Yes, the agent can call getcontractexecutionstatus to verify if a contract transaction failed. It can also use gettxreceiptstatus to double-check the transaction receipt.

Index live Moonbeam ledger data into LlamaIndex vector stores for hallucination-free GLMR and contract analysis.

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Connect Moonscan (Moonbeam Network Explorer) MCP to LlamaIndex

Create your Vinkius account to connect Moonscan (Moonbeam Network Explorer) to LlamaIndex and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Moonscan (Moonbeam Network Explorer) with LlamaIndex

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Index real-time Moonbeam contract source code

This MCP Server allows your LlamaIndex application to ingest and index live smart contract structures directly from Moonscan. The framework uses `get_contract_source_code` to retrieve the raw Solidity code and writes it straight to your vector database. This setup lets LlamaIndex run semantic searches over actual deployed Moonbeam code rather than outdated GitHub repositories. Your RAG queries return exact Moonscan data, ensuring your agent never hallucinates contract structures during an audit.

Synthesize token transfer histories into RAG pipelines

This MCP Server feeds live transactional data directly into your LlamaIndex document stores for historical analysis. By querying `get_erc20_transfers` and `get_erc721_transfers`, your application builds an active knowledge base of asset movements. When a user asks about recent GLMR token activity, the LlamaIndex RAG system queries this index first. This guarantees that your Moonbeam answers are grounded in actual block events rather than pre-trained model weights.

Query Moonbeam block metadata with LlamaIndex agents

This MCP Server connects low-level block data to your knowledge-augmented agents. The agent can verify block production pacing using `get_block_countdown` or fetch specific historical points using `get_block_number_by_time`. This live Moonbeam block context is injected directly into your LlamaIndex prompt window. It allows the LlamaIndex agent to answer time-sensitive questions about Moonbeam network status with absolute precision.

Setup guide

Set up Moonscan (Moonbeam Network Explorer) MCP in LlamaIndex

Prerequisites

Python 3.10+ installed
llama-index-tools-mcp package
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai. The MCP tools package provides BasicMCPClient and McpToolSpec.
2

Connect with BasicMCPClient
Point BasicMCPClient to your Vinkius endpoint URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports SSE and Streamable HTTP transports.
3

Convert to LlamaIndex tools
Call mcp_tool_spec.to_tool_list_async() to convert all Moonscan (Moonbeam Network Explorer) MCP tools into native FunctionTool objects that any LlamaIndex agent can use.
4

Run with any LLM
Create a FunctionAgent with the tools and your preferred LLM. Swap OpenAI for Anthropic, Gemini, or any LlamaIndex-supported provider.

agent.py

from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI

# Connect to the MCP
mcp_client = BasicMCPClient(
    "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)
mcp_tool_spec = McpToolSpec(client=mcp_client)

# Convert MCP tools to LlamaIndex tools
tools = await mcp_tool_spec.to_tool_list_async()

# Create and run the agent
agent = FunctionAgent(
    tools=tools,
    llm=OpenAI(model="gpt-4o"),
    system_prompt="You have access to Moonscan (Moonbeam Network Explorer) tools.",
)
response = await agent.run("List recent Moonscan (Moonbeam Network Explorer) data")

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Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Moonscan. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Moonscan (Moonbeam Network Explorer) MCP in LlamaIndex

Use the `llama-index-tools-mcp` library to initialize the client with your Vinkius URL. Convert the server's tools into a tool spec and pass them to your `FunctionAgent`. This exposes all 26 endpoints, including `get_glmr_balance`, to your agent.

Yes, you can fetch token data using `get_erc20_balance` and insert the resulting balance data directly into your vector index. This allows your RAG pipeline to retrieve updated financial profiles for target addresses on demand.

When calling `get_logs`, the output can be large, so you should use LlamaIndex's node parsers to chunk the data. This prevents your LLM context window from overflowing while keeping the transaction details searchable.

Yes, the agent can call `get_contract_execution_status` to verify if a contract transaction failed. It can also use `get_tx_receipt_status` to double-check the transaction receipt.

Vinkius routes all queries through zero-trust, ephemeral V8 isolates to prevent exposure. Your queried target addresses, GLMR balances, and ABI structures are never cached or inspected. Data flows straight from the Moonscan API to your local LlamaIndex instance over an encrypted connection.

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